Paper Info
Title
Noise estimation in magnetic resonance SENSE reconstructed data.
Abstract
Parallel imaging methods allow to increase the acquisition rate via subsampled acquisitions of the k-space. SENSE is one of the most popular reconstruction methods proposed in order to suppress the artifacts created by this subsampling. However, the SENSE reconstruction process yields to a variance of noise value which is dependent on the position within the image. Hence, the traditional noise estimation methods based on a single noise level for the whole image fail. Accordingly, we propose a novel method to recover the complete spatial pattern of the variance of noise in SENSE reconstructed images up from the sensitivity maps of each receiver coil. Our method fits applications in statistical image processing tasks such as image denoising.
Year
DOI
Venue
2013
10.1109/EMBC.2013.6609698
EMBC
Keywords
Field
DocType
statistical image processing task,noise value variance,traditional noise estimation method,parallel imaging method,acquisition rate,statistics,noise estimation,receiver coil,single noise level,subsampled acquisition,image denoising,spatial pattern,parallel imaging,image reconstruction,sensitivity map,biomedical mri,image sampling,parallel algorithms,sense,k-space,magnetic resonance,sense reconstruction process,artifact suppression,medical image processing,magnetic resonance sense reconstructed data,magnetic resonance imaging,estimation,magnetic resonance spectroscopy,sensitivity,noise,correlation,k space
Median filter,Computer science,Non-local means,Image processing,Electronic engineering,Artificial intelligence,Image restoration,Iterative reconstruction,Computer vision,Pattern recognition,Dark-frame subtraction,Image noise,Digital image processing
Conference
Volume
ISSN
Citations 
2013
1557-170X
1
PageRank 
References 
Authors
0.66
3
4
Name
Order
Citations
PageRank
Santiago Aja-Fernández110.66
Gonzalo Vegas-Sánchez-Ferrero213918.88
Rodrigo de Luis-García315014.15
Antonio Tristán-Vega410.66